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Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

A Pilot Study: Developing a Lactating Dairy Goat Model to Study Staphylococcus aureus Mastitis in Women.

INTRODUCTION: Lactational mastitis is common in lactating women, with Staphylococcus aureus as the most commonly isolated agent associated with infectious lactational mastitis. Currently, there are no evidence-based guidelines for antimicrobial treatment due to barriers in obtaining pharmacokinetic data from lactating women. To overcome this barrier, a suitable large animal model is needed. Goats are an ideal translational model for human mastitis due to their anatomical and physiological similarity to humans. The objective of this pilot study was to assess if goats would develop clinical mastitis following intramammary inoculation with a clinical human isolate of S. aureus with the goal of establishing an alternative in vivo model for future research. The hypothesis was that the infected mammary gland half would show similar clinical signs to women with mastitis and demonstrate a similar local immune response when compared to the control mammary gland half. METHODS: One half of the mammary gland of two healthy lactating does was inoculated with a clinical human isolate of S. aureus. The other half of the mammary gland was sham inoculated with sterile buffered saline. Physical examinations, mammary gland assessments, and sterile milk samples were collected every 12 hours post inoculation. At 96 hours post inoculation, the goats were euthanized, and the mammary glands were examined for pathological changes. RESULTS: Goats did not develop systemic signs of disease following inoculation. Focal infected mammary gland changes included warmth, swelling, redness, discoloration, and reduced milk production; the other mammary gland half remained normal throughout the study period. S. aureus was enumerated from only the infected mammary gland half. The microscopic findings of the infected half showed neutrophilic inflammation and cell necrosis consistent with acute mastitis. DISCUSSION: This pilot study demonstrated lactating does can develop clinical signs like those observed in women. Goats have the potential to be a promising animal model to study infectious lactational mastitis.

Animals

How the Social Context and Peer Helping Contribute to Better Alcohol Outcomes Among Sober Living House Residents: Mediation Analyses.

BACKGROUND: Sober Living Houses (SLHs) adopt a social model approach, which emphasizes peer helping. Although SLHs appear to be effective, little is known regarding why. This longitudinal study examined whether higher SLH social model adherence produces better resident outcomes by increasing resident helping. METHODS: Baselines were conducted with 205 residents entering 28 SLHs, with follow-ups through 6 months. Measures included 1-month perceived SLH social model adherence; 2-month help given to and received from SLH residents; and 6-month alcohol use and severity. Analyses were lagged, multivariate mediation models accounting for clustering within SLH. Separate models examined help given and received for each outcome, yielding four model tests. RESULTS: The hypothesized model was unsupported, with all four tests showing nonsignificant indirect effects. However, exploratory post-hoc tests showed significant indirect effects between higher 1-month resident helping and better 6-month alcohol outcomes via higher 1-month SLH social model adherence. Effects held across three of four model tests. CONCLUSIONS: Results suggest that residences adhering to social model principles do not achieve better outcomes by stimulating helping, but rather that more resident helping may foster a supportive SLH social environment, which itself drives better outcomes. Thus, residences might emphasize both resident helping and social model principles.

Sober living

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals

Modelling peak microbial pollution events caused by combined sewer overflows in a source-to-sea system.

Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10 CFU 100 ml-1)). 99th percentile E. coli concentrations (4.0 (log10 CFU 100 ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10 CFU 100 ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.

Climate projection

Genomic characterization and pathogenicity of ruminant Listeria monocytogenes isolates in a murine oral infection model.

Listeria monocytogenes is a major foodborne pathogen; its ruminant isolates display zoonotic characteristics, causing similar clinical signs in humans, including abortion and encephalitis. However, data on whole genome sequencing and pathogenicity of ruminant L. monocytogenes isolates remain sparse. This study aimed to analyze the genotypic characteristics of L. monocytogenes isolates from ruminants with listeriosis. Furthermore, we assessed the in vivo pathogenicity of four ruminant L. monocytogenes isolates, characterized via whole-genome sequencing-based genetic clustering, in orogastrically inoculated mice. The isolate LM18 (serotype 1/2b, ST224, SL6178) had the lowest lethal dose compared to the other three isolates including previous hypervirulence type (serotype 4b, ST1, SL1) and caused secondary bacteremia in lungs, with sustained bacterial loads in the spleen and liver. Genomic (listeria pathogenicity island -1 and -3) and virulence gene (actA and llsX) mutation analyses associated with virulence suggested from well-recognized studies could not elucidate the virulence of the isolates. SSI-1, which only exists in the isolate LM18 (serotype 1/2b, ST224, SL6178), may help L. monocytogenes survive in the gastrointestinal environment, thereby affecting its virulence. Further research should investigate the role of SSI-1 in the pathogenicity of L. monocytogenes. Moreover, additional studies utilizing larger datasets of ruminant isolates are required to validate our genotypic characterization and to obtain a comprehensive picture of further genotypic differences crucial for L. monocytogenes pathogenicity.

Animals

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation

Prothrombin complex concentrate (PCC) vs. non-PCC strategies for warfarin reversal in left ventricular assist device recipients: A systematic review and meta-analysis.

BACKGROUND: Left ventricular assist devices (LVADs) prolong survival in end-stage heart failure, and warfarin thromboprophylaxis is recommended to prevent device thrombosis and thromboembolic complications. When bleeding occurs or emergency surgery is required, rapid anticoagulation reversal is critical. Prothrombin complex concentrate (PCC) provides rapid reversal; however, its risk-benefit profile in LVAD recipients remains unclear. We conducted a systematic review and meta-analysis comparing PCC with non-PCC strategies for warfarin reversal in LVAD recipients. METHODS: MEDLINE, Embase, and Scopus were searched through June 2025 for studies of PCC versus non-PCC strategies for warfarin reversal in LVAD recipients. Two reviewers independently extracted data. Random-effects models were used to pool arm-level estimates and to pool head-to-head comparisons using mean differences or risk ratios (RRs). RESULTS: Eighteen studies involving 779 patients were included. Arm-level pooled estimates for PCC versus non-PCC comparators were 24.0% versus 15.8% for mortality, 16.5% versus 12.1% for thrombotic events, and 3.1 versus 5.7 for FFP units. Arm-level time to INR correction was longer with PCC overall (16.5 versus 13.6 h), driven by one elective cohort, but faster within the ICH subgroup (6.0 versus 13.7 h). In head-to-head comparisons, PCC achieved faster INR correction than non-PCC comparators (mean difference - 7.6 h; p = 0.001) and required fewer FFP units (-2.6 units; p = 0.019), with no significant difference in all-cause mortality (RR 1.14; p = 0.490) or thrombotic events (RR 1.43; p = 0.176). CONCLUSIONS: In head-to-head studies, PCC was associated with faster INR correction and lower FFP requirements than non-PCC strategies, whereas mortality and thrombotic events did not differ significantly. Given the observational evidence, wide confidence intervals, and heterogeneity, equivalent safety cannot be established, and prospective studies are needed to define the relative safety and effectiveness of the two approaches. IMPLICATIONS FOR CLINICAL PRACTICE: PCC-based strategies may be considered for urgent warfarin reversal in LVAD recipients, particularly when rapid INR reduction or avoidance of large-volume plasma transfusion is clinically important. Treatment decisions should account for the indication, bleeding severity, and underlying thrombotic risk. TRIAL REGISTRATION: CRD42024573925.

Humans

Extending the Treatment Window for Intravenous Thrombolysis in Acute Ischemic Stroke: An Updated Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Intravenous thrombolysis (IVT) is the standard treatment for acute ischemic stroke within 4.5 hours of onset. However, imaging-based selection may extend the treatment window. This systematic review and meta-analysis evaluated the efficacy and safety of IVT administered beyond 4.5 hours after stroke onset or last known well (LKW) in patients selected based on imaging findings. METHODS: A comprehensive search of PubMed, Scopus, and Cochrane Library was performed to identify randomized controlled trials comparing IVT with alteplase or tenecteplase (TNK) administered >4.5 hours after stroke onset/LKW vs standard care. Primary outcomes were 3-month excellent (modified Rankin Scale [mRS] 0-1) functional outcome and symptomatic intracranial hemorrhage (sICH). Secondary outcomes included good (mRS 0-2) functional outcome, recanalization, and 3-month mortality. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models. Subgroup analysis assessed differences between alteplase and TNK. RESULTS: Fourteen studies involving 4,944 patients were included. The mean age was 69.8 years, 58.2% were male, the median National Institutes of Health Stroke Scale score was 9, and 12.3% received preplanned endovascular thrombectomy (EVT). A total of 2,492 patients received IVT in an extended time window (4.5-24 hours). Compared with standard care, extended IVT was associated with higher odds of achieving an excellent functional outcome (OR: 1.43 [95% CI 1.25-1.63]), a good functional outcome (OR: 1.25 [95% CI 1.11-1.40]), and recanalization (OR: 3.28 [95% CI 2.09-5.16]). There was no difference in 3-month mortality (OR: 1.21 [95% CI 0.95-1.53]). However, IVT increased the risk of sICH (OR: 2.51 [95% CI 1.47-4.28]). Sensitivity analysis excluding patients who received EVT showed no impact on the outcomes. TNK exhibited similar efficacy to alteplase but showed potentially lower odds of sICH (OR: 1.96, 95% CI 1.06-3.64) compared with alteplase (OR: 5.29, 95% CI 1.80-15.57); however, the subgroup difference was not significant (p = 0.11). DISCUSSION: Among patients selected based on imaging, 4.5-24 hours after stroke onset/LKW, IVT improves outcomes despite an increased risk of sICH. TNK showed similar efficacy to alteplase, with a possible lower risk of sICH; however, direct comparisons in future trials are needed.

Humans

Efficacy and safety of cannabinoid-based interventions for behavioral and cognitive symptoms in dementia: systematic review and meta-analysis.

BACKGROUND: Behavioral and cognitive symptoms are frequent in Alzheimer's disease and dementia, and available pharmacological options offer limited benefit. Cannabinoid-based therapies have been proposed as alternatives, but evidence remains inconclusive. METHODS: We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library through November 2025 for randomized controlled trials evaluating cannabinoids in Alzheimer's disease or dementia. Primary outcomes were agitation measured by the Cohen-Mansfield Agitation Inventory (CMAI) and neuropsychiatric symptoms assessed by the Neuropsychiatric Inventory-Nursing Home version (NPI-NH). Secondary outcomes included cognition using the Mini-Mental State Examination (MMSE) and adverse events. Standardized Mean Differences (SMDs) and Risk Ratios (RRs) were synthesized using random-effects (REML) and Bayesian random-effects models. Risk of bias was evaluated with RoB 2, and certainty of evidence with GRADE. RESULTS: Nine trials (334 participants) met inclusion criteria. Cannabinoids did not improve CMAI (SMD -0.58, 95% CI -1.71 to 0.55; I2 = 84%), NPI-NH total (SMD -0.02, 95% CI -1.00 to 0.96; I2 = 67%), NPI-NH agitation (SMD -0.44, 95% CI -1.45 to 0.57; I2 = 48%), or MMSE (SMD 0.86, 95% CI -16.33 to 18.06; I2 = 96%). Bayesian posterior estimates were close to zero, supporting the absence of effect. Leave-one-out analyses reduced heterogeneity only after excluding influential trials but did not alter results. Certainty of evidence was moderate for behavioral outcomes and low for cognition. Overall adverse events were similar to placebo, while somnolence was more frequent with cannabinoids (RR 2.03, 95% CI 1.29-3.20). CONCLUSIONS: Cannabinoid-based therapies do not improve agitation, neuropsychiatric symptoms, or cognition in Alzheimer's disease and increase somnolence.

Humans

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. OBJECTIVE: This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. METHODS: Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (&#x2265;5% weight loss, &#x2265;4% weight loss with &#x2265;150 min/week of physical activity, or &#x2265;0.2 percentage point reduction in hemoglobin A1c [HbA1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. RESULTS: Median engagement was 98 (IQR 34-232) days. Older age (P<.001) and lower baseline BMI (P=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; P=.03), &#x2265;5% weight loss (OR 3.31, 95% CI 1.16-9.42; P=.03), and &#x2265;0.2 percentage point reduction in HbA1c (OR 3.57, 95% CI 1.19-10.75; P=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. CONCLUSIONS: Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. TRIAL REGISTRATION: ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376.

Humans

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans

Nurse-led titration models of care for heart failure reduced ejection fraction: a systematic narrative review of characteristics, patient outcomes, and healthcare resource utilization.

AIMS: Nurse-led titration (NLT) models of care assist with delivery of guideline directed medical therapy for patients with heart failure with reduced ejection fraction (HFrEF). Effectiveness of NLT is established but there is limited information of characteristics of models, patient outcomes and healthcare resource utilization. To build upon the existing evidence by providing a systematic narrative review of the literature of NLT of medications for patients with HFrEF. This review syntheses characteristics of NLT models of care, patient outcomes and healthcare resource utilization. METHODS AND RESULTS: A systematic narrative literature review with systematic search strategy, identification of results, thematic analysis and narrative synthesis. A search was conducted from 2012 to 2025 in Medline, Cinahl complete, Embase and Cochrane. Sixteen studies of NLT models of care were identified from 1944 screened records. Characteristics of models of care were participation of nurses, multidisciplinary teams, follow-up and common features of service delivery. Patient outcomes of mortality were favourable for those that received NLT. There is some evidence of changes in healthcare resource utilization; studies in which the NLT groups received more HF nurse visits and greater HF medication use also reported reduced rehospitalizations. CONCLUSION: Findings reinforce the published benefits of NLT. Additional studies examining adverse events and quality-of-life outcomes are needed to strengthen the evidence base. Several studies suggest a shift in resource use with NLT, highlighting the need for an economic evaluation to inform a cost-effective model of care.

Humans

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Evaluating the pathogenic significance of unique chromosomal variants in craniosynostosis using patient-derived induced pluripotent stem cells and mouse modelling.

PURPOSE: Unravelling causal links between unique structural/copy-number variants (SV/CNV) and associated phenotypes is essential for correct genetic counselling. We investigated two families in which patients with craniosynostosis had SV/CNV potentially dysregulating a fibroblast growth factor (FGF)-encoding gene; a 730 kb dup(4)(q21.21) including FGF5; and a complex 568 kb interspersed 13q12.11 duplication, located 841 kb from FGF9. METHODS: We combined bioinformatic predictions of altered topologically-associating domain (TAD) structure, with experimental analysis (RNA- and ATAC- [assay for transposase-accessible chromatin] sequencing) of patient induced pluripotent stem cell lines (iPSCs) differentiated to neural crest (NCC) and osteoprogenitor (OPC) identities. For the dup(4)(q21.21) we generated a mouse bearing an equivalent rearrangement using CRISPR-Cas9 targeting. RESULTS: TAD analysis suggested potential dysregulation of the FGF5/FGF9 gene by bringing it into a novel genomic milieu. The RNA- and ATAC-seq assays demonstrated FGF5/FGF9 upregulation (2.7-18x) and local opening of chromatin, in 3/4 cell lines. For the dup(4)(q21.21), a causal role was supported by the mouse model, whereas interpretation of the 13q12.11 SV is confounded by a co-existing FOXP2 pathogenic variant. CONCLUSION: Patient iPSC-differentiated NCC and OPC lines, combined with TAD-based modelling to generate testable functional hypotheses, provide valuable functional evidence when evaluating causation of unique SV/CNV in craniosynostosis.

copy-number variant

Glucocorticoids and placental 11&#x3b2;HSD2 - A systematic review of human studies and animal models.

CONTEXT: Elevated prenatal glucocorticoid (GC) exposure is linked to adverse offspring outcomes. The placental enzyme 11&#x3b2;-hydroxysteroid-dehydrogenase-type-2 (11&#x3b2;HSD2) protects the fetus by converting maternal derived cortisol to inactive cortisone. Although in vitro studies suggest GC mediated upregulation of 11&#x3b2;HSD2, in vivo evidence remains inconclusive. METHODS: PubMed, Embase, and PsycInfo were searched in October 2024 for human and mammalian animal studies on endogenous or exogenous GCs during pregnancy and associations with placental 11&#x3b2;HSD2 (mRNA, protein, activity, gene methylation). Narrative synthesis was conducted due to heterogeneity precluding meta-analysis. RESULTS: Eighteen studies (eight human, ten animal populations) met inclusion criteria. Exogenous GC exposure was associated with modifications in placental 11&#x3b2;HSD2 expression in animal models, with effects varying by substance, timing, and species. Dexamethasone trended towards increased expression in rodents, whereas betamethasone increased expression in non-human primates but not rodents. Human studies on endogenous GCs showed inconsistent associations with 11&#x3b2;HSD2 changes. In asthmatic pregnancies, moderate inhaled GC-use maintained enzyme activity compared to untreated patients. No convincing sex-specific trend emerged. CONCLUSIONS: GC exposure alters placental 11&#x3b2;HSD2 in a substance- and species-specific way; translational relevance remains limited based on current literature. Future studies should employ technological advances and include GC-sensitive biomarkers to clarify mechanisms of maternal-fetal stress transmission.

Female

Incidence of Cirrhosis in Fibrotic Metabolic Dysfunction-Associated Steatohepatitis: A Meta-Analysis of Placebo Arms from Randomized Clinical Trials.

BACKGROUNDS AND AIMS: Metabolic dysfunction-associated steatohepatitis (MASH) with stage F2-F3 fibrosis represents the main target population for emerging pharmacotherapies. However, data on short-term progression to cirrhosis (F4) in this group remain limited. We aimed to evaluate the incidence of cirrhosis in placebo-treated patients with fibrotic MASH in randomized controlled trials (RCTs). METHODS: In this single-arm meta-analysis, we systematically searched PubMed and Cochrane Library from inception to December 13, 2024, for pharmacological Phase&#x2009;&#x2265;&#x2009;2 RCTs reporting cirrhosis events (detected in liver biopsy or clinical signs) among patients with fibrotic MASH receiving placebo. Incidence rates were pooled using generalized linear mixed models with Clopper-Pearson confidence intervals (CIs). RESULTS: We identified a total of 11 RCTs, including 586 patients with fibrotic MASH. Total follow-up was 657.23 person-years (PYs), with 83 cirrhosis events reported. The pooled incidence rate was 13.09 per 100 PYs (95% CI 7.81 to 21.12, I2&#x2009;=&#x2009;75.6%, &#x3c4;2&#x2009;=&#x2009;0.682). In subgroup analysis, the incidence of cirrhosis was 3.40 per 100 PYs in MASH F2 (95% CI 1.10 to 10.02, I2&#x2009;=&#x2009;0%, &#x3c4;2&#x2009;=&#x2009;0) and 17.90 per 100 PYs (95% CI 10.63 to 28.55, I2&#x2009;=&#x2009;70.2%, &#x3c4;2&#x2009;=&#x2009;0.561) in MASH F3, with significant differences between stages (p&#x2009;=&#x2009;0.006). Sensitivity analyses showed consistent estimates. Most RCTs were judged to have a low risk of bias. CONCLUSIONS: This study provides stage-specific data on cirrhosis incidence in fibrotic MASH, highlighting the high short-term risk associated with MASH F3 in trial settings. These data may inform benchmarks to guide event expectations, enrichment strategies, sample size assumptions, and the interpretation of future MASH clinical trials.

Humans